auto_annot_Haber2017_with_Smillie2019_dblabel

In [1]:
import besca as bc
import pandas as pd
import pkg_resources

./conda/envs/besca_test/lib/python3.6/site-packages/scanpy/api/__init__.py:6: FutureWarning: 

In a future version of Scanpy, `scanpy.api` will be removed.
Simply use `import scanpy as sc` and `import scanpy.external as sce` instead.

  FutureWarning,

Specify folders where .h5ad files are found and their names.

The datasets that are already annotated and should be used for training. If you only use one dataset please use list of one.

In [2]:
# the path to the datasets
train_dataset_paths = [pkg_resources.resource_filename('besca', 'datasets/data')]
#the names of the h5ad files
train_datasets =['Smillie2019_processed.h5ad']

The dataset of interest that should be annotated.

In [3]:
test_dataset = 'haber_processed.h5ad'
test_dataset_path =  pkg_resources.resource_filename('besca', 'datasets/data')

Give your analysis a name.

In [4]:
analysis_name = 'auto_annot_Haber2017_with_Smillie2019_Cluster'

Now specify parameters

Specify column name of celltype annotation you want to train on.

In [5]:
celltype_train ='dblabel' 
celltype_test = 'dblabel'

Choose a method:

  • linear: Support Vector Machine with Linear Kernel
  • sgd: Support Vector Machine with Linear Kernel using Stochastic Gradient Descent
  • rbf: Support Vector Machine with radial basis function kernel. Very time intensive, use only on small datasets.
  • logistic_regression: Standard logistic classifier iwth multinomial loss.
  • logistic_regression_ovr: Logistic Regression with one versus rest classification.
  • logistic_regression_elastic: Logistic Regression with elastic loss, cross validates among multiple l1 ratios.
In [6]:
method = 'logistic_regression'

Specify merge method if using multiple training datasets. Needs to be either scanorama or naive.

In [7]:
merge = 'scanorama'

Decide if you want to use the raw format or highly variable genes. Raw increases computational time and does not necessarily improve predictions.

In [8]:
use_raw = False

You can choose to only consider a subset of genes from a signature set.

In [9]:
genes_to_use = 'all'

Read in all training and the testing set.

In [10]:
adata_trains, adata_pred, adata_orig = bc.tl.auto_annot.read_data(train_paths = train_dataset_paths,train_datasets= train_datasets, test_path=  test_dataset_path, test_dataset= test_dataset, use_raw = use_raw)

Transforming to str index.

Reading files

Transforming to str index.
In [11]:
# Select epithelial subset from Smillie2019 dataset
epithelial_subset = bc.subset_adata(adata_trains[0], adata_trains[0].obs.celltype_highlevel == 'Epi', raw=False)
adata_trains[0] = epithelial_subset
In [12]:
# Convert mouse symbols (MGI) to human symbols (HGNC)
mousehuman_file = pkg_resources.resource_filename('besca', 'datasets/homologs/MGItoHGNC.csv')
mousehuman=pd.read_csv(mousehuman_file,sep='\t',header='infer', encoding="unicode_escape")
mousehuman.index=mousehuman['MGI']
conversion=pd.Series(data=mousehuman['HGNC'], index=mousehuman.index)
In [13]:
# Convert mouse symbols (MGI) to human symbols (HGNC)
adata_orig.var.rename(columns={'SYMBOL':'MGI'}, inplace=True)
adata_orig.var['SYMBOL'] = adata_orig.var['MGI'].map(lambda x: conversion.get(x, default='') if type(conversion.get(x, default='')) == str else conversion.get(x, default=None).values[0])
adata_orig.var.index = adata_orig.var.SYMBOL
adata_orig.var_names_make_unique()
adata_pred = adata_orig.copy()

This function merges training datasets, removes unwanted genes, and if scanorama is used corrects for datasets.

In [14]:
adata_train, adata_pred = bc.tl.auto_annot.merge_data(adata_trains, adata_pred, genes_to_use = genes_to_use, merge = merge)

merging with scanorama
using scanorama rn
Found 273 genes among all datasets
[[0.         0.73639414]
 [0.         0.        ]]
Processing datasets (0, 1)
integrating training set
calculating intersection

Train the classifier.

The returned scaler is fitted on the training dataset (to zero mean and scaled to unit variance).

In [15]:
classifier, scaler = bc.tl.auto_annot.fit(adata_train, method, celltype_train)

[Parallel(n_jobs=10)]: Using backend LokyBackend with 10 concurrent workers.
[Parallel(n_jobs=10)]: Done   5 out of   5 | elapsed:  1.5min finished
./conda/envs/besca_test/lib/python3.6/site-packages/sklearn/linear_model/_logistic.py:940: ConvergenceWarning:

lbfgs failed to converge (status=1):
STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.

Increase the number of iterations (max_iter) or scale the data as shown in:
    https://scikit-learn.org/stable/modules/preprocessing.html
Please also refer to the documentation for alternative solver options:
    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression

Prediction

Use fitted model to predict celltypes in adata_pred. Prediction will be added in a new column called 'auto_annot'. Paths are needed as adata_pred will revert to its original state (all genes, no additional corrections). The threshold should be set to 0 or left out for SVM. For logisitic regression the threshold can be set.

In [21]:
adata_predicted = bc.tl.auto_annot.adata_predict(classifier = classifier, scaler = scaler, adata_pred = adata_pred, adata_orig = adata_orig, threshold = 0.7)

Write out metrics to a report file, create confusion matrices and comparative umap plots

In [22]:
adata_pred.obs
Out[22]:
CELL CONDITION sample_type donor region sample percent_mito n_counts n_genes leiden celltype0 celltype1 celltype2 celltype3 dblabel
haber_intestine_donor_M1_Duo.AAACATACAGCGGA haber_intestine_donor_M1_Duo.AAACATACAGCGGA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.001410 12768.0 1227 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M1_Duo.AAACATACCTTACT haber_intestine_donor_M1_Duo.AAACATACCTTACT healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.010779 6583.0 2156 7 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M1_Duo.AAACATACTTTGCT haber_intestine_donor_M1_Duo.AAACATACTTTGCT healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.033755 2844.0 1424 2 epithelial cell transit amplifying cell transit amplifying cell transit amplifying cell transit amplifying cell
haber_intestine_donor_M1_Duo.AAACCGTGCAGTCA haber_intestine_donor_M1_Duo.AAACCGTGCAGTCA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.022508 2799.0 1362 1 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAACGCTGCAGTCA haber_intestine_donor_M1_Duo.AAACGCTGCAGTCA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.015041 6048.0 2287 5 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAACGCTGCGTGAT haber_intestine_donor_M1_Duo.AAACGCTGCGTGAT healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.023022 2780.0 1320 2 epithelial cell transit amplifying cell transit amplifying cell transit amplifying cell transit amplifying cell
haber_intestine_donor_M1_Duo.AAACGCTGTCCAGA haber_intestine_donor_M1_Duo.AAACGCTGTCCAGA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.007323 9830.0 2909 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M1_Duo.AAACGCTGTTCACT haber_intestine_donor_M1_Duo.AAACGCTGTTCACT healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.000517 23215.0 1093 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M1_Duo.AAACGGCTACACTG haber_intestine_donor_M1_Duo.AAACGGCTACACTG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.001710 23391.0 896 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M1_Duo.AAACGGCTCAACCA haber_intestine_donor_M1_Duo.AAACGGCTCAACCA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.000605 37986.0 1636 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M1_Duo.AAACGGCTCTAAGC haber_intestine_donor_M1_Duo.AAACGGCTCTAAGC healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.003335 5394.0 1732 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M1_Duo.AAACGGCTGTTGCA haber_intestine_donor_M1_Duo.AAACGGCTGTTGCA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.017975 8453.0 2491 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M1_Duo.AAAGACGAACGTTG haber_intestine_donor_M1_Duo.AAAGACGAACGTTG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.003238 7409.0 2019 8 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M1_Duo.AAAGAGACGGCATT haber_intestine_donor_M1_Duo.AAAGAGACGGCATT healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.032794 2468.0 1009 14 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M1_Duo.AAAGCAGAGCGTTA haber_intestine_donor_M1_Duo.AAAGCAGAGCGTTA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.020902 3346.0 1520 10 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAAGGCCTGAGGCA haber_intestine_donor_M1_Duo.AAAGGCCTGAGGCA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.016402 1885.0 1040 4 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAAGGCCTGGAACG haber_intestine_donor_M1_Duo.AAAGGCCTGGAACG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.011500 4253.0 1720 2 epithelial cell transit amplifying cell transit amplifying cell transit amplifying cell transit amplifying cell
haber_intestine_donor_M1_Duo.AAAGTTTGCCATAG haber_intestine_donor_M1_Duo.AAAGTTTGCCATAG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.015288 4313.0 1851 0 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAATACTGCGTACA haber_intestine_donor_M1_Duo.AAATACTGCGTACA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.015411 4022.0 1726 0 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAATACTGGGTGAG haber_intestine_donor_M1_Duo.AAATACTGGGTGAG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.017278 2835.0 1326 10 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAATCCCTAAGCCT haber_intestine_donor_M1_Duo.AAATCCCTAAGCCT healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.016053 8657.0 2660 7 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M1_Duo.AAATCTGAACGGGA haber_intestine_donor_M1_Duo.AAATCTGAACGGGA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.020971 5577.0 2200 5 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAATCTGACGGAGA haber_intestine_donor_M1_Duo.AAATCTGACGGAGA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.008635 6598.0 2150 6 epithelial cell enterocyte progenitor enterocyte progenitor enterocyte progenitor enterocyte progenitor
haber_intestine_donor_M1_Duo.AAATTCGATCGTAG haber_intestine_donor_M1_Duo.AAATTCGATCGTAG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.026409 3671.0 1716 1 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAATTCGATTATCC haber_intestine_donor_M1_Duo.AAATTCGATTATCC healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.019437 11162.0 3220 5 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AAATTGACATCGTG haber_intestine_donor_M1_Duo.AAATTGACATCGTG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.004146 10610.0 1771 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M1_Duo.AACAATACAGGCGA haber_intestine_donor_M1_Duo.AACAATACAGGCGA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.014734 5224.0 2023 6 epithelial cell enterocyte progenitor enterocyte progenitor enterocyte progenitor enterocyte progenitor
haber_intestine_donor_M1_Duo.AACAATACCTGAAC haber_intestine_donor_M1_Duo.AACAATACCTGAAC healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.017134 5305.0 2037 1 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AACACTCTCTGATG haber_intestine_donor_M1_Duo.AACACTCTCTGATG healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.024181 3970.0 1746 0 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M1_Duo.AACACTCTCTGTGA haber_intestine_donor_M1_Duo.AACACTCTCTGTGA healthy mouse_small_intestine_epithelial M1 Duo Duo_M1 0.041631 3457.0 1757 9 epithelial cell enterocyte progenitor enterocyte progenitor enterocyte progenitor enterocyte progenitor
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
haber_intestine_donor_M2_Il.TTCTGATGCTCTAT haber_intestine_donor_M2_Il.TTCTGATGCTCTAT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.004917 2846.0 1309 4 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M2_Il.TTGAATGATGGTTG haber_intestine_donor_M2_Il.TTGAATGATGGTTG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.008567 10968.0 2977 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTGAGGACTGCTGA haber_intestine_donor_M2_Il.TTGAGGACTGCTGA healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.010048 6066.0 2158 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTGAGGTGCTCCCA haber_intestine_donor_M2_Il.TTGAGGTGCTCCCA healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.004893 4492.0 1785 5 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M2_Il.TTGATCTGAGACTC haber_intestine_donor_M2_Il.TTGATCTGAGACTC healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.004664 6644.0 2421 5 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M2_Il.TTGCATTGGGTGAG_1 haber_intestine_donor_M2_Il.TTGCATTGGGTGAG_1 healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.001232 21921.0 2025 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M2_Il.TTGCTAACAAGGCG haber_intestine_donor_M2_Il.TTGCTAACAAGGCG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.015137 2114.0 994 7 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M2_Il.TTGCTAACGCCCTT haber_intestine_donor_M2_Il.TTGCTAACGCCCTT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.015154 5409.0 2261 5 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M2_Il.TTGCTATGATGCCA haber_intestine_donor_M2_Il.TTGCTATGATGCCA healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.009200 7603.0 2210 7 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M2_Il.TTGCTATGCCTAAG haber_intestine_donor_M2_Il.TTGCTATGCCTAAG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.001650 6060.0 1560 8 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTGCTATGCCTGTC haber_intestine_donor_M2_Il.TTGCTATGCCTGTC healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.021724 4412.0 1994 2 epithelial cell transit amplifying cell transit amplifying cell transit amplifying cell transit amplifying cell
haber_intestine_donor_M2_Il.TTGCTATGTAGTCG haber_intestine_donor_M2_Il.TTGCTATGTAGTCG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.004712 3566.0 1466 18 epithelial cell enteroendocrine cell enteroendocrine cell enteroendocrine cell enteroendocrine cell
haber_intestine_donor_M2_Il.TTGCTATGTGGTGT haber_intestine_donor_M2_Il.TTGCTATGTGGTGT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.012014 6406.0 2318 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTGGAGACTTGGTG haber_intestine_donor_M2_Il.TTGGAGACTTGGTG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.008800 4315.0 1808 2 epithelial cell transit amplifying cell transit amplifying cell transit amplifying cell transit amplifying cell
haber_intestine_donor_M2_Il.TTGGTACTAGCCTA haber_intestine_donor_M2_Il.TTGGTACTAGCCTA healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.016637 5647.0 2017 7 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M2_Il.TTGGTACTATCTCT haber_intestine_donor_M2_Il.TTGGTACTATCTCT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.038538 2517.0 1385 4 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M2_Il.TTGGTACTTCGCTC haber_intestine_donor_M2_Il.TTGGTACTTCGCTC healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.008205 3046.0 1317 4 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M2_Il.TTGTAGCTTAGAAG haber_intestine_donor_M2_Il.TTGTAGCTTAGAAG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.009987 8208.0 2341 8 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTGTAGCTTGGAAA haber_intestine_donor_M2_Il.TTGTAGCTTGGAAA healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.007038 4682.0 1939 4 epithelial cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell epithelial fate stem cell
haber_intestine_donor_M2_Il.TTGTCATGTGCTAG haber_intestine_donor_M2_Il.TTGTCATGTGCTAG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.030039 3328.0 1477 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTTAGAGATAGTCG haber_intestine_donor_M2_Il.TTTAGAGATAGTCG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.038527 2932.0 1549 9 epithelial cell enterocyte progenitor enterocyte progenitor enterocyte progenitor enterocyte progenitor
haber_intestine_donor_M2_Il.TTTAGAGATCTACT haber_intestine_donor_M2_Il.TTTAGAGATCTACT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.011722 6563.0 2131 7 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M2_Il.TTTAGCTGAGATGA haber_intestine_donor_M2_Il.TTTAGCTGAGATGA healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.000611 27831.0 1182 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M2_Il.TTTATCCTAACCTG haber_intestine_donor_M2_Il.TTTATCCTAACCTG healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.000712 26674.0 1035 12 epithelial cell paneth cell paneth cell paneth cell paneth cell
haber_intestine_donor_M2_Il.TTTATCCTTGCAGT haber_intestine_donor_M2_Il.TTTATCCTTGCAGT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.011897 4367.0 1726 2 epithelial cell transit amplifying cell transit amplifying cell transit amplifying cell transit amplifying cell
haber_intestine_donor_M2_Il.TTTCAGTGACCAGT haber_intestine_donor_M2_Il.TTTCAGTGACCAGT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.008591 5468.0 2037 2 epithelial cell transit amplifying cell transit amplifying cell transit amplifying cell transit amplifying cell
haber_intestine_donor_M2_Il.TTTCGAACAGAACA haber_intestine_donor_M2_Il.TTTCGAACAGAACA healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.007760 10174.0 2884 7 epithelial cell enterocyte enterocyte enterocyte enterocyte
haber_intestine_donor_M2_Il.TTTCTACTGCTCCT haber_intestine_donor_M2_Il.TTTCTACTGCTCCT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.006121 9307.0 2856 3 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTTGACTGCGCCTT haber_intestine_donor_M2_Il.TTTGACTGCGCCTT healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.007189 4029.0 1277 8 epithelial cell goblet cell goblet cell goblet cell goblet cell
haber_intestine_donor_M2_Il.TTTGCATGGAGGAC haber_intestine_donor_M2_Il.TTTGCATGGAGGAC healthy mouse_small_intestine_epithelial M2 Il Il_M2 0.009316 8907.0 2277 7 epithelial cell enterocyte enterocyte enterocyte enterocyte

12219 rows × 15 columns

In [23]:
%matplotlib inline

bc.tl.auto_annot.report(adata_pred=adata_predicted, celltype=celltype_test, method=method, analysis_name=analysis_name,
                        train_datasets=train_datasets, test_dataset=test_dataset, merge=merge, use_raw=False,
                        genes_to_use=genes_to_use, remove_nonshared=True, clustering='leiden', asymmetric_matrix=True)

./conda/envs/besca_test/lib/python3.6/site-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning:

Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.

./conda/envs/besca_test/lib/python3.6/site-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning:

Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.

... storing 'auto_annot' as categorical

WARNING: saving figure to file figures/umap.ondata_auto_annot_Haber2017_with_Smillie2019_Cluster.png

WARNING: saving figure to file figures/umap.auto_annot_Haber2017_with_Smillie2019_Cluster.png

Confusion matrix, without normalization
Normalized confusion matrix
In [24]:
import scanpy as sc
sc.pl.umap(adata_predicted, color=[celltype_test, 'auto_annot'])
sc.pl.umap(adata_predicted, color=[celltype_test, 'auto_annot'], legend_loc='on data', legend_fontsize=8)
In [25]:
adata_train
Out[25]:
View of AnnData object with n_obs × n_vars = 46102 × 273 
    obs: 'CELL', 'Cluster', 'Health', 'Location', 'Subject', 'celltype_highlevel', 'nGene', 'nUMI', 'original_name', 'percent_mito', 'n_counts', 'n_genes', 'batch', 'leiden', 'dblabel', 'celltype', 'cluster_celltype', 'Type'
    var: 'ENSEMBL-0', 'SYMBOL', 'n_cells-0', 'total_counts-0', 'frac_reads-0', 'ENSEMBL-1', 'MGI-1', 'n_cells-1', 'total_counts-1', 'frac_reads-1'
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